Integration of Artificial Intelligence in the Diagnosis and Prevention of Neurodegenerative Disease: An Update

This chapter discusses the impact of Artificial Intelligence (AI) in medical diagnosis, especially on neurodegenerative diseases. Artificial Intelligence has been gaining attention in medical diagnosis and analysis during the current era. The subdivisions of AI have proved remarkable achievements in the medical diagnostic purposes and have been accepted by many medical centers in aiding the treatment processes. The high computational skills of AI and its computational time required for the processing are making AI systems more efficient and acceptable in the community. Neurodegenerative diseases are many in types and vary accordingly with individual subjects. Dealing with medical data and processing the medical data is highly complex. Data which is in various forms warrants specific normalization before processing. Complex medical data requires expert knowledge to understand and process the research problem. AI has expanded in multidimensional processing with many learning neural networks like Convolutional Neural Network, Recurrent Neural Network, VGG Network, and many more. Depending on the data, the network needs to get trained and then identify the best suited network which can handle the data processing to obtain the required results. The training time required by the network varies with respect to the chosen neural network and its structuring. During the validation process, the networks acceptance can be known with the percentage of accuracy. The review of the research findings for neurodegenerative diseases using AI has shown the future scope of how the medical diagnostic process could advance further.